In a pipelined machine if an instruction is dependent on the result of another one, a pipeline stall will happen where the pipeline will stop, waiting for the offending instruction to finish before resuming work. This is especially a problem in iterative arithmetic coding processes such as JPEG2000, JPEG, On2, and in H.264 Context-based Adaptive Binary Arithmetic Coding (CABAC). For example H.264 CABAC is based on the principle of recursive interval subdivision. [For a full description of the H264 CABAC standards and details see ITU-T Series H: Audiovisual and Multimedia Systems Infrastructure of audiovisual—coding of moving video] Given a probability estimation p(0) and p(1)=1−p(0) of a binary decision (0,1), an initially given interval or range will be subdivided into two sub-intervals having a range*p(0) and range-range*p(0), respectively. Depending on the decision, the corresponding sub-interval will be chosen as the new code interval, and a binary code string pointing to that interval will present the sequence of binary decisions. It is useful to distinguish between the most probable symbol (MPS) and the least probable symbol (LPS), so that binary decisions are identified as either MPS or LPS, rather then 0 or 1. According to H.264 CABAC process the range and state are used to access a two dimensional look-up table to determine the rLPS (range of least probable symbol). Current range is derived from the rLPS and the previous range. If the code offset (Value) is less than the current range, the Most probable path is taken where the most probable symbol (MPS) is designated as the next output bit, and the state transition is preformed based on the most probable symbol (MPS) look-up table. If Value is greater than current range, the Least probable path is taken where the MPS bit is inverted, the current Value is determined from the previous Value and the range then rLPS is assigned to range. Following this, if the state equals zero, the MPS is inverted. The next state transition is derived from the LPS state table based on the current state, followed by the renormalization process where the range is then renormalized to the [511,256] interval. This is done by left-shifting range the required amount of bits. Value must be left shifted the same amount of bits. Value bits that are shifted out constitute the output of the arithmetic coder. The problem with the normalization procedure is that some times a carry bit is produced during the Value updating. This carry bit can propagate to parts of the code that have been already issued. Thus, the outstanding bits mechanism is implemented so that output bit is suspended until it is clear that future carry bits will not propagate to already-emitted parts of the code. Basically, any bit with a value ‘0’ will stop the carry propagation. The aforesaid routines and algorithms, as well as many others require a great deal of computation and are vulnerable to pipeline stall. Yet in this and many other algorithms, there are preferred paths or most probable solutions or primary operational sequences of operation which require numerous cycles of operation to accomplish yet whose output is fairly predictable.